| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn shouted again [again]" |
| | dialogueSentences | 43 | | tagDensity | 0.674 | | leniency | 1 | | rawRatio | 0.034 | | effectiveRatio | 0.034 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1531 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 54.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1531 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "weight" | | 1 | "gloom" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "depths" | | 5 | "velvet" | | 6 | "scanned" | | 7 | "etched" | | 8 | "flickered" | | 9 | "silence" | | 10 | "echo" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 209 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 209 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 223 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1531 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 26 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1391 | | uniqueNames | 9 | | maxNameDensity | 3.09 | | worstName | "Quinn" | | maxWindowNameDensity | 9.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Quinn | 43 | | Morris | 12 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Police" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0 | | windowScore | 0 | |
| 98.45% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | glossingSentenceCount | 2 | | matches | | 0 | "graffiti that seemed to shift when she wasn't looking directly at it" | | 1 | "sounded like it came from everywhere at on" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.653 | | wordCount | 1531 | | matches | | 0 | "not from the suspect, but from the shadows lining the tunnel walls" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 223 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 90 | | mean | 17.01 | | std | 14.89 | | cv | 0.875 | | sampleLengths | | 0 | 64 | | 1 | 11 | | 2 | 60 | | 3 | 33 | | 4 | 10 | | 5 | 38 | | 6 | 55 | | 7 | 35 | | 8 | 38 | | 9 | 49 | | 10 | 21 | | 11 | 18 | | 12 | 50 | | 13 | 19 | | 14 | 2 | | 15 | 23 | | 16 | 4 | | 17 | 19 | | 18 | 33 | | 19 | 15 | | 20 | 37 | | 21 | 29 | | 22 | 4 | | 23 | 56 | | 24 | 5 | | 25 | 13 | | 26 | 10 | | 27 | 36 | | 28 | 57 | | 29 | 27 | | 30 | 6 | | 31 | 10 | | 32 | 8 | | 33 | 18 | | 34 | 15 | | 35 | 14 | | 36 | 15 | | 37 | 4 | | 38 | 31 | | 39 | 20 | | 40 | 29 | | 41 | 27 | | 42 | 26 | | 43 | 10 | | 44 | 9 | | 45 | 38 | | 46 | 12 | | 47 | 3 | | 48 | 8 | | 49 | 8 |
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| 95.19% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 209 | | matches | | 0 | "were buried" | | 1 | "were cracked" | | 2 | "was gone" | | 3 | "was etched" | | 4 | "was gone" | | 5 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 275 | | matches | | 0 | "wasn't looking" | | 1 | "was already moving" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 223 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1392 | | adjectiveStacks | 2 | | stackExamples | | 0 | "heavy, cold against her" | | 1 | "heavy, pressing against her" |
| | adverbCount | 16 | | adverbRatio | 0.011494252873563218 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0028735632183908046 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 223 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 223 | | mean | 6.87 | | std | 4.18 | | cv | 0.608 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 13 | | 3 | 18 | | 4 | 6 | | 5 | 5 | | 6 | 16 | | 7 | 12 | | 8 | 15 | | 9 | 11 | | 10 | 6 | | 11 | 16 | | 12 | 13 | | 13 | 4 | | 14 | 10 | | 15 | 14 | | 16 | 5 | | 17 | 5 | | 18 | 6 | | 19 | 8 | | 20 | 10 | | 21 | 12 | | 22 | 11 | | 23 | 8 | | 24 | 5 | | 25 | 9 | | 26 | 8 | | 27 | 9 | | 28 | 9 | | 29 | 9 | | 30 | 7 | | 31 | 8 | | 32 | 4 | | 33 | 19 | | 34 | 8 | | 35 | 6 | | 36 | 14 | | 37 | 6 | | 38 | 12 | | 39 | 3 | | 40 | 4 | | 41 | 9 | | 42 | 5 | | 43 | 3 | | 44 | 10 | | 45 | 4 | | 46 | 4 | | 47 | 7 | | 48 | 6 | | 49 | 15 |
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| 37.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 29 | | diversityRatio | 0.2242152466367713 | | totalSentences | 223 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 181 | | matches | (empty) | | ratio | 0 | |
| 78.56% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 64 | | totalSentences | 181 | | matches | | 0 | "Her breath came in short," | | 1 | "She didn't call out a" | | 2 | "She didn't waste the breath." | | 3 | "She ignored the sting in" | | 4 | "She didn't slow down." | | 5 | "They turned down a narrow" | | 6 | "She didn't draw it yet." | | 7 | "She needed to keep her" | | 8 | "She shoved it aside, the" | | 9 | "Her eyes adjusted to the" | | 10 | "She knew the stories." | | 11 | "She knew the entry requirement." | | 12 | "They knew the way." | | 13 | "She stepped onto the first" | | 14 | "Her heart hammered against her" | | 15 | "She had chased a shadow" | | 16 | "She had found a room" | | 17 | "It sounded like it came" | | 18 | "They had melted into the" | | 19 | "She looked at her watch." |
| | ratio | 0.354 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 175 | | totalSentences | 181 | | matches | | 0 | "Rain lashed against the pavement," | | 1 | "Harlow Quinn drove her boots" | | 2 | "Her breath came in short," | | 3 | "The figure ahead wore a" | | 4 | "She didn't call out a" | | 5 | "She didn't waste the breath." | | 6 | "Quinn pushed off the wall," | | 7 | "The worn leather of her" | | 8 | "She ignored the sting in" | | 9 | "DS Morris died because of" | | 10 | "The suspect ducked under a" | | 11 | "Quinn vaulted over a stack" | | 12 | "She didn't slow down." | | 13 | "Quinn shouted, the word snatched" | | 14 | "The figure glanced back, eyes" | | 15 | "Recognition sparked in Quinn's chest." | | 16 | "This wasn't a random thief." | | 17 | "This was someone from the" | | 18 | "Someone who knew where the" | | 19 | "They turned down a narrow" |
| | ratio | 0.967 | |
| 82.87% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 181 | | matches | | 0 | "If she went down, she" | | 1 | "If she went down, she" | | 2 | "If she stayed, the suspect" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 1 | | matches | | 0 | "Vendors sold jars of liquid that glowed in the dark, vials of powder that shifted color, and books bound in skin." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn shouted, the word snatched away by the wind" |
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| 98.28% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 29 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "Quinn shouted again (shout)" | | 2 | "Morris corrected (correct)" |
| | dialogueSentences | 43 | | tagDensity | 0.674 | | leniency | 1 | | rawRatio | 0.103 | | effectiveRatio | 0.103 | |